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Development of causal graph for hazardous chemical accidents
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Hongru LI1, Tingting LUAN1, **, Mingyue DENG1, Wentao CHEN2, Xue ZHANG1
China Safety Science Journal | 2024, 34(5) : 195 - 203
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China Safety Science Journal | 2024, 34(5): 195-203
Safety engineering technology
Development of causal graph for hazardous chemical accidents
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Hongru LI1, Tingting LUAN1, **, Mingyue DENG1, Wentao CHEN2, Xue ZHANG1
Affiliations
  • 1 School of Safety Engineering,Beijing Institute of Petrochemical Technology,Beijing 102617,China
  • 2 Information Research Institute,Emergency Management Department,Beijing 100029,China
Published: 2024-05-28 doi: 10.16265/j.cnki.issn1003-3033.2024.05.1570
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The causality causal graph of hazardous chemical accidents was developed to improve the safety management level of hazardous chemical enterprises. Firstly,based on the accident investigation report,an entity-relationship joint extraction model was proposed through an improved CasRel technique. Furthermore,the proposed model aimed to improve the extraction accuracy of textual information by incorporating the relationship-aware bidirectional encoder representation method (R-Bert) and Span pointer network. Subsequently,similarity calculation methods were used to generalize the events to enhance the graph's comprehensiveness and accuracy. Then,the refined data was stored in the Neo4j graph database visualizing the associations between events. Finally,the corresponding guestion-answering system was proposed based on the developed causal graph,and then an intelligent question-answering system for the causality of hazardous chemical accidents was proposed. The results indicated that the F1 value calculated by the improved CasRel model was 90.5%,and the prediction accuracy of the proposed model was 2% higher than that simulated by the original model. The hazardous chemical accidents causal graph and intelligent question-answering system performed well in terms of multiple evaluation indexes,clearly revealing the logical relationship between events. Therefore,the proposed model in this study can meet question-answering needs of hazardous chemical accidents,facilitating the exploration of accident patterns and potential risk factors,and enabling accident trend prediction.

hazardous chemical accidents  /  casual graph  /  knowledge extraction  /  causality  /  intelligent question-answering system
Hongru LI, Tingting LUAN, Mingyue DENG, Wentao CHEN, Xue ZHANG. Development of causal graph for hazardous chemical accidents[J]. China Safety Science Journal(CSSJ), 2024 , 34 (5) : 195 -203 . DOI: 10.16265/j.cnki.issn1003-3033.2024.05.1570
Year 2024 volume 34 Issue 5
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2024.05.1570
  • Receive Date:2023-11-14
  • Online Date:2025-07-14
  • Published:2024-05-28
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History
  • Received:2023-11-14
  • Revised:2024-02-21
Affiliations
    1 School of Safety Engineering,Beijing Institute of Petrochemical Technology,Beijing 102617,China
    2 Information Research Institute,Emergency Management Department,Beijing 100029,China
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表12种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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